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We introduce the Hardy–Weinberg principle, which is the fundamental model of population genetics. The use of mathematical models is essential to understand the effects of Mendelian inheritance and the evolution of allele frequencies in natural populations. The Hardy–Weinberg model assumes random mating, infinite population size, no natural selection, no mutation, and no immigration. There are two primary outcomes of the Hardy–Weinberg model: (1) Hardy–Weinberg equilibrium and (2) Hardy–Weinberg proportions. Testing for Hardy–Weinberg proportions in population samples is usually the first step in describing genotypic variation in natural populations. We consider several explanations for why genotypic proportions might not be in Hardy–Weinberg proportions. The Hardy–Weinberg model is useful for estimating allele frequencies in natural populations. We describe two measures for comparing the amount of genetic variation in natural populations: heterozygosity and allelic richness.

Loss of biodiversity is among the greatest problems facing the world today. Conservation and the Genomics of Populations gives a comprehensive overview of the essential background, concepts, and tools needed to understand how genetic information can be used to conserve species threatened with extinction, and to manage species of ecological or commercial importance. New molecular techniques, statistical methods, and computer programs, genetic principles, and methods are becoming increasingly useful in the conservation of biological diversity. Using a balance of data and theory, coupled with basic and applied research examples, this book examines genetic and phenotypic variation in natural populations, the principles and mechanisms of evolutionary change, the interpretation of genetic data from natural populations, and how these can be applied to conservation. The book includes examples from plants, animals, and microbes in wild and captive populations. This third edition has been thoroughly revised to include advances in genomics and contains new chapters on population genomics, genetic monitoring, and conservation genetics in practice, as well as new sections on climate change, emerging diseases, metagenomics, and more. More than one-third of the references in this edition were published after the previous edition. Each of the 24 chapters and the Appendix end with a Guest Box written by an expert who provides an example of the principles presented in the chapter from their own work. This book is essential for advanced undergraduate and graduate students of conservation genetics, natural resource management, and conservation biology, as well as professional conservation biologists and policy-makers working for wildlife and habitat management agencies. Much of the book will also interest nonprofessionals who are curious about the role of genetics in conservation and management of wild and captive populations.

Genetics is the study of the inheritance of differences among individuals. Genomic approaches now make it possible to better understand the genetic basis and adaptive significance of phenotypic differences among individuals. Population-level differences in disease resistance will have important implications for population persistence in the face of emergent infectious diseases. In addition, understanding the genomic basis for that phenotype will be crucial for conservation efforts such as genetically informed breeding for reintroductions, genetic rescue of infected populations, and population restoration following declines. Most phenotypic differences between individuals within populations have both genetic and environmental causes. Raising individuals from different populations in the same environmental conditions can be used to test if there is a genetic component to phenotypic differences among populations. Understanding and maintaining phenotypic differences between individuals within populations and between populations can play a crucial role in conservation.

Genetics plays an increasing role in monitoring demographic and genetic changes in populations over time. One of the most powerful advances in genetic monitoring is the development of techniques to detect trace amounts of DNA in noninvasive samples (e.g., feathers, skin, etc.) and environmental DNA (eDNA) from elusive and rare species in water and soil samples. Individual genotypes from noninvasive samples such as feces and hair can be used to estimate abundance, survival, and other demographic parameters using mark–recapture analysis. Genetic monitoring of heterozygosity, allelic diversity, and effective population size allows managers to detect genetic changes in response to environmental perturbations or management actions. Genomic methods now allow detection and monitoring of adaptive alleles; for example, to test whether these alleles increase in frequency in response to environmental change, demonstrating an adaptive response, stress, or a die-off (e.g., caused by infectious disease pathogens).

Captive breeding represents the last chance of survival for many species faced with imminent extinction in the wild. Captive breeding should be used sparingly because it is sometimes ineffective, and it can harm wild populations both indirectly and directly if not done correctly. There are a variety of crucial genetic issues to be considered in the founding of captive populations: How many individuals? Which source population(s)? A primary genetic goal of captive breeding programs is to minimize genetic change in captivity due to genetic drift and selection because genetic changes in captive populations can reduce the ability of captive individuals to reproduce and survive when returned to the wild. A variety of potentially valuable technologies (e.g., cloning, CRISPR-Cas (clustered regularly interspaced short palindromic repeats-CRISPR-associated system), gene drives, etc.) are now available that have the potential to be valuable tools in conservation.

Most phenotypic traits are the product of many genes as well as environmental effects, and the resulting phenotypic variation is quantitative rather than qualitative. The extent to which traits are under genetic control is termed heritability, and can be estimated by analyzing the phenotypic similarity of related individuals. Quantitative genetic approaches can be used to estimate population differentiation. Selection on quantitative traits produces changes in phenotypes as a function of the heritability, the intensity of selection, and the amount of phenotypic variation within a population. Human activities, such as size-limited harvesting and habitat degradation, can impose selection on natural populations and result in changes in phenotypes, and genetic drift in small populations can erode quantitative genetic variation. Genome-wide association studies can identify genes and markers associated with quantitative trait variation that can then be used to predict phenotypes from polygenic scores.

Population genetic models become much more complex when two or more loci are considered simultaneously. Random association of the alleles (and genotypes) at two loci is called gametic equilibrium. Linkage is the primary factor that can cause the alleles at two loci to be in nonrandom association within a population. This is called gametic disequilibrium. Many other factors (e.g., genetic drift, selection, hybridization, etc.) can cause even unlinked loci to be in gametic disequilibrium. The interpretation of multilocus genotypes is becoming increasingly important in conservation because of advances in techniques to screen many loci and advances in data analysis. The ability to sequence large sections of chromosomes provides the opportunity to interpret multiple locus genetic data using entirely new conceptual approaches. It is now possible to use sequence data to identify chromosomal segments originating from different ancestral chromosomes.

There is mounting evidence that human exploitation of wild populations can lead to genetic changes that greatly increase the complexity of managing sustainable populations. Harvest can reduce the effective population size and cause loss of genetic variation by reducing population size directly and by reducing the number of migrants into local populations. Harvest tends to remove phenotypes that are most desirable, which can reduce the frequency of these phenotypes by artificial selection. Even random harvest will select for earlier sexual maturity. Harvest of wild populations can perturb genetic subdivision among populations and reduce overall productivity. The harvest of a group of individuals that is a mixture of several subpopulations can result in the extirpation of one or more subpopulations. Exploitation of wild animals and plants often depends upon augmentation through releases of translocated or captive-raised individuals. Such releases can bring about adverse genetic change to wild populations.

All populations are finite in size so that genetic drift will occur in all natural and managed populations. Genetic drift causes both changes in allele frequencies and the loss of genetic variation. Loss of heterozygosity and loss of alleles are t^ghe two primary measures of the loss of genetic variation in populations. Matings between related individuals (i.e., inbreeding) is more common in small populations, and this will lead to inbreeding depression in small populations. Understanding the effects of genetic drift is especially important for conservation because loss of genetic variation and inbreeding depression can reduce the probability of population persistence.

Hybridization occurs between species or populations, and can arise from either natural or anthropogenic causes. Hybridization is important in natural evolutionary processes, but can be a harmful force reducing species identity and reproductive success. Hybridization can increase fitness through heterosis, or reduce fitness through outbreeding depression. Genetic analysis can effectively identify hybridization and has frequently used diagnostic loci that have different allele frequencies in the parents. Hybrid indices or admixture analyses use proportions of parental ancestry in individuals to identify hybrids. Hybridization contributes to decline and extinction of species through loss of reproductive potential and reduced population growth, or through genetic mixing and loss of genetically distinct populations. Determining whether hybridization is natural or anthropogenic is crucial for conservation. Protection of hybrids is often based on whether they are genetically distinct through long-term isolation or speciation, or whether they represent recent, ongoing, or anthropogenic hybridization.

Mutations are errors in the transmission of genetic information from parents to progeny, and an understanding of mutation assists in interpreting patterns of genetic variation to inform conservation. Mutation is the source of all variation, and can be neutral, beneficial, or detrimental. Mutation rates vary across the nuclear genome, and are generally higher in animal mitochondrial genomes, but much lower in chloroplast and plant mitochondrial genomes. Mutation contributes to variation within populations, population subdivision, and the rate of recovery from bottlenecks. Mutations can be detected using genomic analysis, or through effects on morphological, physiological, or behavioral traits. The amount of standing genetic variation within populations is a balance between the gain of genetic variation from mutations and loss from genetic drift. Natural selection acts to keep mutations that have a detrimental effect on fitness from increasing in frequency, and genetic drift aids the survival of advantageous mutations.

Sequencing all or part of the genome of individuals from different populations allows for many analyses of genetic variation that are not possible with a small number of unlinked markers. Genomic datasets may include sequences of anonymous regions scattered throughout the genome, sequences of targeted regions such as exomes, whole genome sequences, or genotypes for single nucleotide polymorphisms (SNPs) or other targeted polymorphisms. Fully sequenced reference genomes were previously limited to model organisms and crop species, but can now be produced for any species, facilitating development of species-specific tools and sophisticated analyses. Next-generation sequencing can also quantify variation in gene expression, identify changes in DNA structure such as methylation involved in epigenetic responses, and characterize the multispecies metagenomics of communities and environments. While generating large genomic datasets has become much easier and faster, population genomic analyses now require stronger bioinformatic skills and more powerful computational resources.

Populations may respond to environmental changes through phenotypic plasticity, adaptation, migration, or suffer demographic declines if they are unable to respond. Climate change is already causing shifts in species ranges, changes in phenotypes, and altered life history traits and interspecific interactions. The capacity for a population to adapt to new conditions is a function of the amount of genetic and phenotypic variation for traits under selection, fecundity, and the rate of environmental change per generation. Several genomic approaches are available for predicting the extent of maladaptation of populations resulting from climate change based on the mismatch between genotypes and new climates. The conservation of populations that are threatened by rapid climate change may in some cases require management tools including assisted gene flow to facilitate adaptation, and greater connectivity of habitats to facilitate range shifts and migration (i.e., gene flow).

In this chapter, we discuss the importance of and methods for delineating conservation units, including species and intraspecific units (e.g., evolutionarily significant units and management units). It is essential to conserve all levels of biodiversity, including genes, populations, species, and ecosystems, for effective biodiversity conservation. Phylogenies—evolutionary trees that depict the patterns and timing of branching events in the evolutionary history of taxa—are an essential concept and tool for delineating species. Genetic and genomic data also play a key role in defining populations and the relationships among individuals and populations within species. Genetic relationships can be depicted using a variety of population- or individual-based analyses. Phenotypic and environmental data should be integrated with genetic and genomic data for robust inference of conservation units.

Genetic factors affect the extinction probability of populations in a variety of ways. Inbreeding depression can reduce fecundity and survival, and thereby decrease population growth rate and increase extinction probability. Multiple studies have shown that inbreeding depression can negatively impact populations in the wild. Loss of genetic variation in small populations also decreases the capacity of populations to evolve to changing environmental conditions. Population viability analysis is a modeling approach that integrates information on demography, genetics, threats, and management actions to predict population persistence. Genomics will advance incorporation of genetic factors into predicting extinction risk by improving our ability to estimate inbreeding depression and evolutionary potential.

We are living in a time of unprecedented loss of biodiversity. Genetics and genomics can play a crucial role in protecting biodiversity. Conservation is an effort to protect the genetic and taxonomic diversity that has been produced by evolution over the past 3.5 billion years. Extinction is a demographic process, but the likelihood of extinction can be reduced by applying an understanding of genetics. Conservation genetics has origins beginning with Darwin. Although the field has become extremely broad, most published articles and applications dealing with conservation and genetics fit into one of five general categories described in this chapter. This is an exciting time to be interested in the genetics of populations. New technologies are promising to advance conservation, from managing wild and captive populations to tracking invasive species and pathogens. The application of innovative genetic technologies will play an important role in biodiversity conservation long into the future.

Genetic variation among individuals within populations and among populations can be assessed at the chromosomal, protein, or DNA sequence level. The best tool or approach depends on the question being asked. Variation in the number or structure of chromosomes can result in reproductive incompatibilities and reduced fitness that influences the success of conservation efforts. Differences in amino acid sequence that alter the electrophoretic mobility of proteins, termed allozymes, were widely used to measure genetic variation and population differentiation on a gene-by-gene basis prior to advances in DNA sequencing. Mitochondria and chloroplasts contain circular DNA molecules that are usually inherited from one parent and are useful for assessing population history and structure. Most studies of genetic variation now rely on the analysis of single nucleotide polymorphisms (SNPs)—variations in nucleotides at a single location within the genome—to understand both selectively neutral and adaptive processes.

We expect heterozygosity to be lost at a rate of 1/2N per generation in an ideal population because of genetic drift where N is the census population size. The effective size of a population is the size of the ideal (Wright–Fisher) population that will result in the same amount of genetic drift as in the actual population being considered. Heterozygosity is generally lost at a rate much faster than 1/2N in natural populations primarily because reproductive success is much more variable than assumed in an ideal population. Therefore, the effective size of natural populations (N e) is often much smaller than the census population size (N e << N). Predicting the rate of loss of heterozygosity over calendar time in a population requires an estimate of both N e and the generation interval. Genomic techniques provide a variety of methods to estimate N e in natural populations.

Natural selection is the differential contribution of genotypes to the next generation due to differences in survival and reproduction. Understanding the effects of natural selection on allele frequencies involves using a variety of mathematical models along with the fitness of different genotypes. Finesses are not constant. For example, fitness sometimes changes when allele frequencies change. Frequency-dependent selection is a powerful mechanism for maintaining genetic variation in natural populations. Natural selection is less effective in small populations because genetic drift can swamp the effects of differential survival or fertility. Understanding the interaction between natural selection and genetic drift is crucial for the conservation of natural and managed populations.

Natural populations of most species are subdivided or “structured” into partially isolated local random mating populations that are called “demes.” The subdivision of a species into subpopulations means that genetic variation exists at two levels: (1) genetic variation within local populations and (2) genetic diversity between local populations. The amount of divergence among populations is a function of the amount of gene flow between populations, the effective population sizes (i.e., genetic drift), and fitness differences in different environments (i.e., natural selection). In some species, individuals are distributed continuously across large landscapes (e.g., coniferous tree species across boreal forests) and are not subdivided into discrete subpopulations by barriers to gene flow (isolation by distance). Understanding the patterns and extent of genetic divergence among populations is crucial for protecting species and developing effective conservation plans. For example, translocations may have harmful effects if the translocated individuals are genetically different from the recipient population.

Invasive species have significant effects on biodiversity. Genetics provides insights important for eradication and control crucial for conservation. Invasive species can be successful despite bottlenecks because of increased genetic diversity following hybridization or multiple introductions, rapid evolutionary change, lack of natural enemies, or absence of constraints from local adaptation. Genetic and genomic analysis can identify cryptic invasive species, sources of introductions, pathways of spread, and patterns of adaptation and invasion. Bottlenecked species will have less diversity in the invasive range than in the native range, and species with multiple introductions will have greater diversity than in the native range. Genetic analysis can identify the mode of reproduction, including clonality, selfing, or parthenogenesis/apomixis. Invasive species detection is a crucial first step in determining prevalence of disease vectors. Metagenomics and metabarcoding can detect parasites and pathogens, and track the origin and transmission of parasites and infectious diseases.

Populations may respond to environmental changes through phenotypic plasticity, adaptation, or migration, or suffer demographic declines if they are unable to respond. Climate change is already causing shifts in species ranges, changes in phenotypes, and altered interspecific interactions. The capacity for a population to adapt to new conditions is a function of the amount of phenotypic variation for traits under selection, fecundity, and the rate of environmental change per generation. Several genomic approaches are available for predicting the extent of maladaptation of populations resulting from climate change based on the mismatch between genotypes and new climates. The conservation of populations that are threatened by rapid climate change may in some cases require management tools including assisted gene flow to facilitate adaptation, and greater connectivity of habitats to facilitate migration.

Genetic analysis allows genetic identification of individuals, populations, and species for a range of conservation purposes, including wildlife trafficking, detecting invasive species, determining relatedness in captive breeding, and identifying community composition. Genomics provides increased power for genetic identification at individual, population, and species levels, and is a key tool in wildlife forensics. DNA barcoding using specific markers has become common for species identification, and metabarcoding of environmental or mixed samples through genomics informs community composition, diet analysis, and identifying cryptic, elusive, or rare individuals and species. Genetic identification has become prominent in wildlife forensics providing critical evidence to enable prosecutions and deter illegal wildlife activities. Multilocus genotyping allows determination of parentage and relatedness, population assignment, and origin of samples. Determination of the relatedness or parentage of individuals provides information on identification of dispersal and migration patterns, and facilitates management of captive breeding populations.

Whereas a rich literature exists for estimating population genetic divergence, metrics of phenotypic trait divergence are lacking, particularly for comparing multiple traits among three or more populations. Here, we review and analyze via simulation Hedges’ g, a widely used parametric estimate of effect size. Our analyses indicate that g is sensitive to a combination of unequal trait variances and unequal sample sizes among populations and to changes in the scale of measurement. We then go on to derive and explain a new, non-parametric distance measure, “Δp”, which is calculated based upon a joint cumulative distribution function (CDF) from all populations under study. More precisely, distances are measured in terms of the percentiles in this CDF at which each population’s median lies. Δp combines many desirable features of other distance metrics into a single metric; namely, compared to other metrics, p is relatively insensitive to unequal variances and sample sizes among the populations sampled. Furthermore, a key feature of Δp—and our main motivation for developing it—is that it easily accommodates simultaneous comparisons of any number of traits across any number of populations. To exemplify its utility, we employ Δp to address a question related to the role of sexual selection in speciation: are sexual signals more divergent than ecological traits in closely related taxa? Using traits of known function in closely related populations, we show that traits predictive of reproductive performance are, indeed, more divergent and more sexually dimorphic than traits related to ecological adaptation [Current Zoology 58 (3): 423-436, 2012].